Cardiovascular Risk Prediction Models and Scores in the Era of Personalized Medicine

Abstract

Cardiovascular disease (CVD) is the leading cause of death worldwide. Management of cardiovascular risk factors, particularly hypertension and dyslipidemia, has been shown to reduce cardiovascular morbidity and mortality. However, current guidelines recommend adjusting the intensity of blood pressure- and lipid-lowering treatment according to the cardiovascular risk of the patient. Therefore, cardiovascular risk prediction is a sine qua non for optimizing cardiovascular prevention strategies, particularly in patients without established CVD or type 2 diabetes mellitus (T2DM). As a result, several cardiovascular risk prediction equations have been developed. Nevertheless, it is still unclear which is the optimal prediction risk equation. In the present review, we summarize the current knowledge regarding the accuracy of the most widely used cardiovascular risk prediction equations. Notably, most of these risk scores have not been validated in external cohorts or were shown to over- or underestimate risk in populations other than those in which they derive. Accordingly, country-specific risk scores, where available, should be preferred for cardiovascular risk stratification.